Next generation automotive systems such as Lane Departure Warning (LDW), Collision Avoidance (CA), Blind Spot Detection (BSD) or Adaptive Cruise Control (ACC) systems will require target information from multiple sensors including a new class of sensor called sensor apertures such as radar, image or laser, similar to those found on advanced tactical fighter aircraft. For example, one sensor aperture may be located on the front bumper of the vehicle and obtains range and azimuth information about vehicles and stationary objects in front of the vehicle. Another sensor aperture may be located on the dash of the vehicle and obtains image information about vehicles and stationary objects in front of the vehicle. Another sensor aperture may be located on the side of the vehicle and obtains either range and azimuth data or image data in order to determine velocity and track information on vehicles that pass the vehicle. These new systems must take all of the information from the multiple sensors apertures on the vehicle and compute an accurate picture of the moving objects around the vehicle; this is known as kinematic state of the targets, or Situation Awareness (SA). To do this the Situation Awareness Platform (SAP) must accurately align the sensors apertures to each other so that information about a target from one sensor aperture can be used with information about the target from a different sensor aperture. This is called Sensor Fusion (SF), this is necessary for the SAP to get an optimal kinematic state of the targets around the vehicle in order to assess threat. The sensor apertures must also be aligned to the body of the vehicle so that the SAP can determine the position and velocity of the target with respect to the vehicle; this is called Navigation Fusion (NF).
One method of aligning the sensors apertures to each other and to the vehicle is to use mechanical and optical instruments, such as auto-collimators and laser boresight tools, during the production of the vehicle. This technique is not only costly, but would be require if a sensor aperture were repaired or replaced after production. An alignment procedure would have to be performed again in order to assure the safety critical systems were reporting accurately. Also as the vehicle goes through normal wear and tear the sensor apertures would start to become misaligned and may not be noticed by the operator. This means that the data from the sensor apertures would not correlate with each other and the vehicle reference frame until the sensor apertures were aligned again. Again, this would be costly to the vehicle operator and until performed, the SAP may not provide accurate data. Therefore, a method to align the sensor apertures to each other and to the vehicle without the use of sophisticated optical tools is required. This patent addresses this problem by describing methods that can be used to align the sensor apertures to each other and to the vehicle that do not require external alignment equipment.
In a discussion of Prior Art, U.S. Pat. No. 5,245,909, Automatic Sensor Alignment, relates to systems for maintaining alignment-sensitive aircraft-borne avionics and weapons sensors in precise alignment. It further relates to methods for precisely aligning sensitive avionics for weapons system instrumentation, which is subject to vibrations causing misalignment. Whereas this disclosure relates to methods and systems that support advanced automotive systems not described in the prior art. A second key difference is the reliance of sensor data from the vehicle as part of the alignment method. Another difference is using image apertures with elements of the vehicle in the field of view of the imager and employing optical methods for determining changes to the alignment with respect to the vehicle and vehicle reference frame, then applying a compensation based on the misalignment angle measured. Finally, this system described herein does not require a reliance on boresighting and aligning any sensor to achieve a vehicle reference frame.
U.S. Pat. No. 6,202,027, Automatic Curve Sensor Calibration, describes an improved system for accurately determining the travel path of a host vehicle and the azimuth angle of a target vehicle through an automatic calibration that detects and compensates for misalignment and curve sensor drift. The difference is a reliance on observed objects and track file generation and subsequent changes to the track files over time. Whereas this patent teaches methods of alignment based force vectors, rotational rates or optically measured changes with respect to the vehicle reference frame. Essentially all observed objects are compensated for misalignment error on the observing vehicle.
U.S. Pat. No. 5,031,330, Electronic Boresight, teaches that pairs of level sensing devices can be used in a method that aligns plane surfaces to one another by tilting platforms equal to the amount misalignment measured to adjust the sensor azimuth. Whereas this patent teaches that the sensor apertures are rigidly mounted to the vehicle and correction to misalignment is done by compensation values observed with respect to the vehicle reference frame.
Different sensors can be used in vehicles to identify objects and possible collision conditions. For example, there may be an optical sensor, such as a camera, mounted to the roof of the vehicle. Another Infrared (IR) sensor may be mounted in the front grill of the vehicle. A third inertial sensor may be located in yet another location in the central portion of the vehicle. Data from these different sensors is correlated together to identify and track objects that may come within a certain vicinity of the vehicle.
The measurements from the different sensors must be translated to a common reference point before the different data can be accurately correlated. This translation is difficult because the sensors are positioned in different locations on the vehicle. For example, the sensor located inside the front bumper of the vehicle may move in one direction during a collision while the sensor located on the top of the vehicle roof may move in a different direction.
One of the sensors may also experience vibrations at a different time than the other sensor. For example, the front bumper sensor may experience a vertical or horizontal movement when the vehicle runs over an obstacle before any movements or vibrations are experienced by the roof sensor. This different movements of sensors relative to each other make is very difficult to accurately determine the precise position and orientation of the sensors when the sensor readings are taken. This makes it difficult to translate the data into common reference coordinates.
The present invention addresses this and other problems associated with the prior art.